Consideration and Disclosure of Group Risks in Genomics and Other Data-Centric Research: Does the Common Rule Need Revision?
Authors: Carolyn Riley Chapman, Gwendolyn P. Quinn, Heini M. Natri, Courtney Berrios, Patrick Dwyer, Kellie Owens, Síofra Heraty, Arthur L. Caplan
Journal: The American Journal of Bioethics (2023)

AbstractHarms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements in the informed consent process; and criteria for waivers of informed consent. In accordance with respect for persons and communities, investigators and IRBs should systematically consider potential group harm when designing and reviewing protocols, respectively. Research participants should be informed about any potential group harm in the consent process. We call for additional public discussion, empirical research, and normative analysis on these issues to determine the right regulatory and policy path forward.Keywords: Group harminformed consentinstitutional review boardresearch ethicsbig datagenetic researchgenomic research ACKNOWLEDGMENTSWe thank the anonymous reviewers who provided constructive feedback and suggestions which improved the paper. We also thank the Autism Intervention Research Network on Physical Health (AIR-P) for facilitating the Ethics in Genetics and Autism Research (EGAR) workgroup, which connected CRC, HMN, PD and SH. We thank other members of EGAR for productive discussions which were helpful as we developed this paper.DISCLOSURE STATEMENTNo potential conflict of interest was reported by the authors.Notes1 We chose to use ‘data-centric’ rather than closely related terms ‘big data’ or ‘data-driven,’ mainly because exploitative group harms can result from ‘small data’ as well as ‘big data’ approaches. Also, in the context of bioethics, data-driven might be confused with empirical research, which is a broader category (e.g., inclusive of interventional clinical trials). For further exploration of the definitions of these terms and epistemological implications, see (Leonelli Citation2016).2 The FDA’s Exception from Informed Consent (EFIC) pathway for emergency research permits higher-than-minimal-risk research that would not meet criteria for a waiver of consent, to improve treatment options for patients who are facing life-threatening health emergencies and are unable to provide consent due to incapacitation (See Weijer, Goldsand, and Emanuel Citation1999; Feldman et al. Citation2019). Notably, informing communities about the planned research and seeking comments from community members is a required component of EFIC (DHHS and FDA [2011] 2013). The IRB must take community feedback into consideration when reviewing the protocol (DHHS and FDA Citation1996).3 Whether IRBs should consider risks arising from research results was “intensively debated” by the National Commission and at some institutions, including UC Berkeley; ultimately, the Commission’s recommendations (and the regulations) precluded IRB consideration of risks from research results (Gray Citation1980). Gray noted that “The issue, however, remains very troublesome, and will, I suspect, continue to be seriously debated in the future” (1980, 4).4 Referring to language in the federal regulations about IRBs not evaluating long-term social risks of research, Klitzman notes “Presumably, the regulations’ intent is that social risks should not stand in the way of the science” (Klitzman Citation2013, 7). A similar rationale can be extended to the informed consent process.5 Sometimes, e.g., when disabled children have non-disabled caregivers, the individuals charged with making decisions about consent to research participation may not even belong to categories of people that are most strongly impacted by its results.6 For instance, there has been debate in the National Institutes of Health All of Us program about the appropriateness of enrolling American Indian/Alaska Native (AI/AN) individuals who may be living in urban, non-Tribal areas: “All data from self-identified AI/AN individuals is being withheld from the public and from researchers, and data will not be released until AI/AN participants have had time to learn more about the results of this [Tribal] consultation and make an informed decision about continuing in the All of Us Research Program” (NIH All of US Citation2021). For additional discussion, see (TCWG 2018). In the context of autism genomics research, Leneh Buckle, an autistic autism researcher, agreed to serve as a freelance Co-Lead on the Spectrum 10K community consultation, despite her awareness “of the criticisms of any autistic person who is willing to associate themselves with a genetic research project” (Hopkins and Buckle Citation2022); this scope of criticism would thus also cover research participants themselves.7 We acknowledge this creates the need to determine and define minimal risk to third parties, groups and communities, which may be a challenge. In the context of individuals, minimal risk is defined by the FDA as meaning that “the probability and magnitude of harm or discomfort anticipated in the research are not greater in and of themselves than those ordinarily encountered in daily life or during the performance of routine physical or psychological examinations or tests” (FDA Citation2014).Additional informationFundingCB’s work on this manuscript was supported by a Clinical and Translational Science Award (CTSA) grant from the National Center for Advancing Translational Sciences (NCATS) awarded to the Frontiers Clinical and Translational Science Institute at the University of Kansas (#UL1TR002366). KO’s work is supported by the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH) (grant #R00HG010905). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH or NCATS.